DATA DRIVEN MANUFACTURING WITH IIOT

SKZ optimizes processes and improves product quality with unprecedented machine data insights

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Case Study Highlights

Unmatched product quality through machine learning

✓ Shopfloor data available in real-time

✓ Significant decrease in rejects

✓ Improved product quality

INDUSTRY

Plastic solutions

EMPLOYEES

430+

PRODUCTION SITES

Challenges

Lack of data lowers production quality and increases waste

Narrow temperature window for optimum product quality
Inaccurate measurement due to lack of sensors in the centre of the melt
High reject rate and lower production quality

Solution

Machine learning model provides data insights

Integration and centralization of data from various sources and sensors using Cybus Connectware
Machine learning model based on the data obtained
Deriving recommendations via a visual dashboard

CYBUS CONNECTWARE

Scalable data architecture for digital manufacturing

End-to-end data transparency and OT-IT integration – for every step towards smart factory transformation
Scalable data architecture for digital projects without limits
All IIoT projects integrated by a single software – independent of interfaces and manufacturers

BENEFITS

A better understanding of the production process is the key to first-class product quality

Shopfloor data available

The machine learning model and real-time availability of shop floor data is a significant leap in optimizing plastic production processes.

Decrease in rejects

Obtaining and processing crucial machine data that was previously inaccessible leads to more efficient and higher quality production with significantly less rejects.

Improved product quality

This advancement optimizes products and solves market challenges, advancing intelligent manufacturing in the plastics industry.

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Leading manufacturers trust in Connectware

Metal processing | Automotive | Machine and tool construction | Agricultural machinery

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